Evidence mapPaperPMID 40133288Full record

ArticleNature communications2025

Leveraging large-scale biobank EHRs to enhance pharmacogenetics of cardiometabolic disease medications.

Marie C Sadler, Alexander Apostolov, Caterina Cevallos, Chiara Auwerx, Diogo M Ribeiro, Russ B Altman, Zoltán Kutalik

Abstract read
In one paragraph

Article in Nature communications, 2025. 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. A systematic review of real-world evidence on the clinical relevance, characterization, and utility ofJournal of pharmacy & pharmaceutical sciences : a publication of the Canadian Society for Pharmaceutical Sciences, Societe canadienne des sciences pharmaceutiques · 2025
    Pooled it
  2. Polygenic Prediction of Nongoal Response to Statin Therapy.Circulation. Genomic and precision medicine · 2026
    Article
  3. Polygenic risk scores in pharmacogenomics: methodological challenges, current applications, and perspectives for clinical implementation.Medizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V · 2026
    Article
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  12. G protein-coupled receptor digital twins for precision and personalized medicine.Computational and structural biotechnology journal · 2025
    Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Marie C SadlerUniversity Center for Primary Care and Public Health, Lausanne, Switzerland.ORCID http://orcid.org/0000-0002-2599-9207
Alexander ApostolovDepartment of Computational Biology, University of Lausanne, Lausanne, Switzerland.ORCID http://orcid.org/0009-0003-1159-5652
Caterina CevallosCenter for Integrative Genomics, University of Lausanne, Lausanne, Switzerland.ORCID http://orcid.org/0000-0002-6708-091X
Chiara AuwerxUniversity Center for Primary Care and Public Health, Lausanne, Switzerland.ORCID http://orcid.org/0000-0003-3613-8450
Diogo M RibeiroDepartment of Computational Biology, University of Lausanne, Lausanne, Switzerland.ORCID http://orcid.org/0000-0002-0482-7342
Russ B AltmanDepartment of Bioengineering, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0003-3859-2905
Zoltán KutalikUniversity Center for Primary Care and Public Health, Lausanne, Switzerland. zoltan.kutalik@unil.ch.ORCID http://orcid.org/0000-0001-8285-7523

Funding

PharmGKB: pharmacogenomics discovery and implementationU24HG010615 · NHGRI · STANFORD UNIVERSITY · 2022 to 2025
$4.2M
Computational methods for characterizing sources of variability in drug responseR35GM153195 · STANFORD UNIVERSITY · 2025 to 2025
$348k
NHGRI NIH HHS U24 HG010615NIGMS NIH HHS R35 GM153195Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation) 310030_189147U.S. Department of Health & Human Services | National Institutes of Health (NIH) HG010615
6 · The paper itself

Abstract

Electronic health records (EHRs) coupled with large-scale biobanks offer great promises to unravel the genetic underpinnings of treatment efficacy. However, medication-induced biomarker trajectories stemming from such records remain poorly studied. Here, we extract clinical and medication prescription data from EHRs and conduct GWAS and rare variant burden tests in the UK Biobank (discovery) and the All of Us program (replication) on ten cardiometabolic drug response outcomes including lipid response to statins, HbA1c response to metformin and blood pressure response to antihypertensives (N = 932-28,880). Our discovery analyses in participants of European ancestry recover previously reported pharmacogenetic signals at genome-wide significance level (APOE, LPA and SLCO1B1) and a novel rare variant association in GIMAP5 with HbA1c response to metformin. Importantly, these associations are treatment-specific and not associated with biomarker progression in medication-naive individuals. We also found polygenic risk scores to predict drug response, though they explained less than 2% of the variance. In summary, we present an EHR-based framework to study the genetics of drug response and systematically investigated the common and rare pharmacogenetic contribution to cardiometabolic drug response phenotypes in 41,732 UK Biobank and 14,277 All of Us participants.

Indexed as

Biological Specimen BanksCardiovascular DiseasesElectronic Health RecordsPharmacogeneticsAgedAntihypertensive AgentsFemaleGenome-Wide Association StudyGlycated HemoglobinHumansHydroxymethylglutaryl-CoA Reductase InhibitorsMaleMetforminMiddle AgedPolymorphism, Single NucleotideUnited KingdomAntihypertensive AgentsGlycated Hemoglobinhemoglobin A1c protein, humanHydroxymethylglutaryl-CoA Reductase InhibitorsMetformin

Identifiers

PMID40133288
PMCPMC11937416

What Socratic holds

Texttitle and abstract
LicenceCC BY
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 Socratic graph.