Evidence map›Paper›PMID 39637863›Full record

ArticleCell genomics2024

Characterizing the genetic architecture of drug response using gene-context interaction methods.

Michal Sadowski, Mike Thompson, Joel Mefford, Tanushree Haldar, Akinyemi Oni-Orisan, Richard Border, Ali Pazokitoroudi, Na Cai, Julien F Ayroles, Sriram Sankararaman and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Polygenic Prediction of Nongoal Response to Statin Therapy.Circulation. Genomic and precision medicine · 2026
    Article
  5. Context-specific genetic effects inform endotypes and treatment in asthma.The Journal of allergy and clinical immunology · 2026
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Choice of phenotype scale is critical in biobank-based G×E tests.bioRxiv : the preprint server for biology · 2026
    Article
  11. Article
  12. Article
  13. Article
  14. Beyond predictive RAmerican journal of human genetics · 2025
    Article
  15. Review
  16. Review
  17. 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

12 authors.

Michal SadowskiBioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA 90095, USA. Electronic address: michalsadowski@ucla.edu.
Mike ThompsonBioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA 90095, USA.
Joel MeffordDepartment of Neurology, University of California Los Angeles, Los Angeles, CA 90095, USA.
Tanushree HaldarInstitute for Human Genetics, University of California San Francisco, San Francisco, CA 94143, USA; Department of Clinical Pharmacy, University of California San Francisco, San Francisco, CA 94143, USA.
Akinyemi Oni-OrisanInstitute for Human Genetics, University of California San Francisco, San Francisco, CA 94143, USA; Department of Clinical Pharmacy, University of California San Francisco, San Francisco, CA 94143, USA.
Richard BorderDepartment of Neurology, University of California Los Angeles, Los Angeles, CA 90095, USA; Department of Computer Science, University of California Los Angeles, Los Angeles, CA 90095, USA; Department of Computational Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA.
Ali PazokitoroudiDepartment of Computer Science, University of California Los Angeles, Los Angeles, CA 90095, USA.
Na CaiHelmholtz Pioneer Campus, Helmholtz Munich, 85764 Neuherberg, Germany; Computational Health Centre, Helmholtz Munich, 85764 Neuherberg, Germany; School of Medicine and Health, Technical University of Munich, 80333 Munich, Germany.
Julien F AyrolesDepartment of Ecology and Evolution, Princeton University, Princeton, NJ 08544, USA; Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA.
Sriram SankararamanBioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA 90095, USA; Department of Computer Science, University of California Los Angeles, Los Angeles, CA 90095, USA; Department of Computational Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA; Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA.
Andy W DahlSection of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL 60637, USA.
Noah ZaitlenBioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA 90095, USA; Department of Neurology, University of California Los Angeles, Los Angeles, CA 90095, USA; Department of Computational Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA; Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA. Electronic address: nzaitlen@ucla.edu.

Funding

Methods for Genome-wide Association Studies in Admixed PopulationsR01HG006399 · NHGRI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI PRICE, ALKES L · 2011 to 2024
$6.3M
A path to personalized phenotypic prediction: unlocking the context-dependency of allelic effectsR35GM124881 · NIGMS · UNIVERSITY OF CALIFORNIA BERKELEY · PI Julien Ayroles · 2017 to 2026
$3.7M
Improved methods for inference of genotype-specific response to environmental toxinsR01ES029929 · NIEHS · PRINCETON UNIVERSITY · PI AYROLES, JULIEN, CLARK, ANDREW G · 2019 to 2023
$3.6M
Novel statistical genetics methods to unravel polygenic interactions in complex traitsR35GM150822 · NIGMS · UNIVERSITY OF CHICAGO · PI Andrew Dahl · 2023 to 2026
$1.6M
Expressive and scalable statistical models for genomic and biomedical dataR35GM153406 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Sriram Sankararaman · 2024 to 2026
$1.0M
NHGRI NIH HHS R01 HG006399NIEHS NIH HHS R01 ES029929NIGMS NIH HHS R35 GM124881NIGMS NIH HHS R35 GM150822NIGMS NIH HHS R35 GM153406
6 · The paper itself

Abstract

Identifying factors that affect treatment response is a central objective of clinical research, yet the role of common genetic variation remains largely unknown. Here, we develop a framework to study the genetic architecture of response to commonly prescribed drugs in large biobanks. We quantify treatment response heritability for statins, metformin, warfarin, and methotrexate in the UK Biobank. We find that genetic variation modifies the primary effect of statins on LDL cholesterol (9% heritable) as well as their side effects on hemoglobin A1c and blood glucose (10% and 11% heritable, respectively). We identify dozens of genes that modify drug response, which we replicate in a retrospective pharmacogenomic study. Finally, we find that polygenic score (PGS) accuracy varies up to 2-fold depending on treatment status, showing that standard PGSs are likely to underperform in clinical contexts.

Indexed as

WarfarinBlood GlucoseCholesterol, LDLFemaleGenetic VariationGlycated HemoglobinHumansHydroxymethylglutaryl-CoA Reductase InhibitorsMaleMetforminMethotrexateMultifactorial InheritancePharmacogeneticsRetrospective StudiesBlood GlucoseCholesterol, LDLGlycated HemoglobinHydroxymethylglutaryl-CoA Reductase InhibitorsMetforminMethotrexateWarfaringene-environment interactionsgenetic heterogeneitygenetic testingheritabilityheteroskedasticitypersonalized medicinepharmacogenomics

Identifiers

PMID39637863
PMCPMC11701255

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.