Genome-wide associations spanning 194 in-hospital drug dosage change phenotypes highlight diverse genetic backgrounds in concurrent drug therapy
As populations get older and medicine consumption rises, the rate of concurrent drug use and polypharmacy among patients is increasing. Polypharmacy is known to complicate therapy and increase the risk of drug-drug interactions, the individuality of which remain largely unexplored. Here, we perform...
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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-01-01
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| Series: | Computational and Structural Biotechnology Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2001037025002582 |
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| Summary: | As populations get older and medicine consumption rises, the rate of concurrent drug use and polypharmacy among patients is increasing. Polypharmacy is known to complicate therapy and increase the risk of drug-drug interactions, the individuality of which remain largely unexplored. Here, we perform a series of genome-wide association studies to identify variants associated with dosage changes during episodes of concurrent drug therapy. We extracted in-hospital drug prescription records from 847,537 patients in a population-wide Danish hospital cohort. Using imputed genotype data from the Copenhagen Hospital Biobank and the Danish Blood Donor Study we then performed a series of genome-wide association analyses across 194 drug pair phenotypes fulfilling selection criteria. We identified 51 genome-wide significant (p < 5E-08) loci, 49 so far unreported in any genome-wide association studies, associated with dosage changes across 42 different drug pair phenotypes. 49 of the identified loci were unique to the respective drug pairs. Through annotation of the identified loci, expression quantitative trait loci analyses, and gene-based tests we found links to 57 distinct genes, several of which have previously been associated with disease. This study identifies genes that may modulate response to drug therapy in the context of polypharmacy. Our findings reveal distinct patterns of genetic variation across different drug pairs, suggesting a diverse set of genes involved in drug efficacy and drug response. This study may give a better understanding of the individuality of such mechanisms and may aid the development personalized treatment approaches. |
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| ISSN: | 2001-0370 |