Polygenic and pharmacogenomic contributions to medication dosing: a real-world longitudinal biobank study
Abstract Background Understanding interindividual variability in medication dosing is central to precision medicine. Despite significant pharmacogenomic (PGx) insights into key biological pathways influencing drug response, the polygenic contribution to dose variability and the potential of electron...
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BMC
2025-07-01
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| Series: | Journal of Translational Medicine |
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| Online Access: | https://doi.org/10.1186/s12967-025-06782-y |
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| author | Silva Kasela Laura Birgit Luitva Kristi Krebs Estonian Biobank Research Team Märt Möls Lili Milani Maris Alver |
| author_facet | Silva Kasela Laura Birgit Luitva Kristi Krebs Estonian Biobank Research Team Märt Möls Lili Milani Maris Alver |
| author_sort | Silva Kasela |
| collection | DOAJ |
| description | Abstract Background Understanding interindividual variability in medication dosing is central to precision medicine. Despite significant pharmacogenomic (PGx) insights into key biological pathways influencing drug response, the polygenic contribution to dose variability and the potential of electronic health records for maintenance dose estimation remain largely unexplored. Methods We leveraged longitudinal drug purchase data linked to the Estonian Biobank (N = 212,000) to derive individual-level daily doses per purchase as well as median and maximum doses as consolidated metrics across purchases for cardiovascular and psychiatric drugs: statins, warfarin, metoprolol, antidepressants, and antipsychotics. Associations with polygenic scores (PGSs) for 16 traits were assessed using linear mixed models and multivariable regression with a forward stepwise approach. Genome-wide association studies (GWAS) were followed by gene set enrichment analyses for known PGx genes. Results Sample sizes ranged from 684 (antipsychotics) to 20,642 (statins), with median doses reflecting typical maintenance doses. Trait-specific PGSs were significant for the daily dose of statins (coronary heart disease PGS, β = 0.02, P = 5.9 × 10–10) and metoprolol (systolic blood pressure PGS, β = 0.03, P = 7.5 × 10–13). The PGS for body mass index was linked to daily doses of statins (β = 0.02, P = 6.4 × 10–7), metoprolol (β = 0.03, P = 1.4 × 10–14), and warfarin (β = 0.03, P = 0.001), whereas the PGS for educational attainment showed opposing associations with statins (β = − 0.01, P = 5.9 × 10–4) and antidepressants (β = 0.01, P = 0.002). Median and maximum doses yielded similar, though generally weaker, associations. GWAS confirmed signals for metoprolol (CYP2D6, P = 1.1 × 10–20) and warfarin (CYP2C9, P = 8.9 × 10–60; VKORC1, P = 4.2 × 10–148), as well as enrichment of PGx signals for individual statins (P = 0.02 for simvastatin, P = 0.03 for atorvastatin). Associations remained significant after adjusting for disease-specific PGSs, suggesting independent contributions of PGx loci. Conclusions These findings illustrate the feasibility and value of leveraging real-world electronic health records to derive pharmacologically meaningful medication dosing phenotypes. Both polygenic and pharmacogenomic signals contribute to dose variability, underscoring their potential utility in personalized prescribing strategies. |
| format | Article |
| id | doaj-art-4d1da31e013f40e0b5cbad7cfbdcc395 |
| institution | DOAJ |
| issn | 1479-5876 |
| language | English |
| publishDate | 2025-07-01 |
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| spelling | doaj-art-4d1da31e013f40e0b5cbad7cfbdcc3952025-08-20T03:04:15ZengBMCJournal of Translational Medicine1479-58762025-07-0123111510.1186/s12967-025-06782-yPolygenic and pharmacogenomic contributions to medication dosing: a real-world longitudinal biobank studySilva Kasela0Laura Birgit Luitva1Kristi Krebs2Estonian Biobank Research TeamMärt Möls3Lili Milani4Maris Alver5Estonian Genome Centre, Institute of Genomics, University of TartuEstonian Genome Centre, Institute of Genomics, University of TartuEstonian Genome Centre, Institute of Genomics, University of TartuEstonian Genome Centre, Institute of Genomics, University of TartuEstonian Genome Centre, Institute of Genomics, University of TartuEstonian Genome Centre, Institute of Genomics, University of TartuAbstract Background Understanding interindividual variability in medication dosing is central to precision medicine. Despite significant pharmacogenomic (PGx) insights into key biological pathways influencing drug response, the polygenic contribution to dose variability and the potential of electronic health records for maintenance dose estimation remain largely unexplored. Methods We leveraged longitudinal drug purchase data linked to the Estonian Biobank (N = 212,000) to derive individual-level daily doses per purchase as well as median and maximum doses as consolidated metrics across purchases for cardiovascular and psychiatric drugs: statins, warfarin, metoprolol, antidepressants, and antipsychotics. Associations with polygenic scores (PGSs) for 16 traits were assessed using linear mixed models and multivariable regression with a forward stepwise approach. Genome-wide association studies (GWAS) were followed by gene set enrichment analyses for known PGx genes. Results Sample sizes ranged from 684 (antipsychotics) to 20,642 (statins), with median doses reflecting typical maintenance doses. Trait-specific PGSs were significant for the daily dose of statins (coronary heart disease PGS, β = 0.02, P = 5.9 × 10–10) and metoprolol (systolic blood pressure PGS, β = 0.03, P = 7.5 × 10–13). The PGS for body mass index was linked to daily doses of statins (β = 0.02, P = 6.4 × 10–7), metoprolol (β = 0.03, P = 1.4 × 10–14), and warfarin (β = 0.03, P = 0.001), whereas the PGS for educational attainment showed opposing associations with statins (β = − 0.01, P = 5.9 × 10–4) and antidepressants (β = 0.01, P = 0.002). Median and maximum doses yielded similar, though generally weaker, associations. GWAS confirmed signals for metoprolol (CYP2D6, P = 1.1 × 10–20) and warfarin (CYP2C9, P = 8.9 × 10–60; VKORC1, P = 4.2 × 10–148), as well as enrichment of PGx signals for individual statins (P = 0.02 for simvastatin, P = 0.03 for atorvastatin). Associations remained significant after adjusting for disease-specific PGSs, suggesting independent contributions of PGx loci. Conclusions These findings illustrate the feasibility and value of leveraging real-world electronic health records to derive pharmacologically meaningful medication dosing phenotypes. Both polygenic and pharmacogenomic signals contribute to dose variability, underscoring their potential utility in personalized prescribing strategies.https://doi.org/10.1186/s12967-025-06782-yReal-world health dataElectronic Health RecordsBiobankMedication dosingPharmacogenomicsGenome-wide association study |
| spellingShingle | Silva Kasela Laura Birgit Luitva Kristi Krebs Estonian Biobank Research Team Märt Möls Lili Milani Maris Alver Polygenic and pharmacogenomic contributions to medication dosing: a real-world longitudinal biobank study Journal of Translational Medicine Real-world health data Electronic Health Records Biobank Medication dosing Pharmacogenomics Genome-wide association study |
| title | Polygenic and pharmacogenomic contributions to medication dosing: a real-world longitudinal biobank study |
| title_full | Polygenic and pharmacogenomic contributions to medication dosing: a real-world longitudinal biobank study |
| title_fullStr | Polygenic and pharmacogenomic contributions to medication dosing: a real-world longitudinal biobank study |
| title_full_unstemmed | Polygenic and pharmacogenomic contributions to medication dosing: a real-world longitudinal biobank study |
| title_short | Polygenic and pharmacogenomic contributions to medication dosing: a real-world longitudinal biobank study |
| title_sort | polygenic and pharmacogenomic contributions to medication dosing a real world longitudinal biobank study |
| topic | Real-world health data Electronic Health Records Biobank Medication dosing Pharmacogenomics Genome-wide association study |
| url | https://doi.org/10.1186/s12967-025-06782-y |
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