| Title: | A Genetic Analysis of Current Medication Use in the UK Biobank |
| Journal: | Journal of Personalized Medicine |
| Published: | 20 Mar 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/38541061/ |
| DOI: | https://doi.org/10.3390/jpm14030319 |
| URL: | https://www.mdpi.com/2075-4426/14/3/319/pdf?version=1710913871 |
Publication 10080
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Abstract
Genomics has been forecasted to revolutionise human health by improving medical treatment through a better understanding of the molecular mechanisms of human diseases. Despite great successes of the last decade's genome-wide association studies (GWAS), the results have been translated to genomic medicine to a limited extent. One route to get closer to improved medical treatment could be by understanding the genetics of medication use. Current medication profiles from 335,744 individuals from the UK Biobank were obtained, and a GWAS was conducted to identify common genetic variants associated with current medication use. In total, 59 independent loci were identified for medication use, and approximately 18% of the total variation was attributable to common genetic variation. The largest fraction of genetic variance for current medication use was captured by variants with low-to-medium minor allele frequency, with coding, conserved genomic regions and transcription start sites being enriched for associated variants. The average correlation (R) between medication use and the polygenic score was 0.14. The results further demonstrated that individuals with higher polygenic burden for medication use were, on average, sicker and had a higher risk for adverse drug reactions. These results provide an insight into the genetic contribution of medication use and pave the way for developments of novel multiple trait polygenic scores, which include the genetically informed medication use.</p>
1 Author
- Palle Duun Rohde
1 Application
| Application ID | Title |
|---|---|
| 31269 | Genomic feature prediction models |
Enabling scientific discoveries that improve human health