ArticleNature communications2025
Leveraging large-scale biobank EHRs to enhance pharmacogenetics of cardiometabolic disease medications.
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.
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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.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- 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 · 2025Pooled it
- Polygenic Prediction of Nongoal Response to Statin Therapy.Circulation. Genomic and precision medicine · 2026Article
- Polygenic risk scores in pharmacogenomics: methodological challenges, current applications, and perspectives for clinical implementation.Medizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V · 2026Article
- Pharmacogenomic predictors of drug response and choice in dyslipidemia and hypertension.medRxiv : the preprint server for health sciences · 2026Article
- Oral and cardiometabolic health through the lens of biobanks and large-scale epidemiologic research.Frontiers in oral health · 2026Review
- Understanding the causes and consequences of low statin adherence: evidence from UK Biobank primary care data.BMC medicine · 2025Article
- Polygenic and pharmacogenomic contributions to medication dosing: a real-world longitudinal biobank study.Journal of translational medicine · 2025Article
- Incorporating genetic data improves target trial emulations and informs the use of polygenic scores in randomized controlled trial design.Nature genetics · 2025Article
- Association between plausible genetic factors and weight loss from GLP1-RA and bariatric surgery.Nature medicine · 2025Article
- Combining cross-sectional and longitudinal genomic approaches to identify determinants of cognitive and physical decline.Nature communications · 2025Article
- Association between plausible genetic factors and weight loss from GLP1-RA and bariatric surgery: a multi-ancestry study in 10 960 individuals from 9 biobanks.medRxiv : the preprint server for health sciences · 2025Article
- G protein-coupled receptor digital twins for precision and personalized medicine.Computational and structural biotechnology journal · 2025Review
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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.
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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.