Rohde Palle Duun
Genomic Medicine, Department of Health Science and Technology, Aalborg University, 9220 Aalborg, Denmark.
J Pers Med. 2024 Mar 20;14(3):319. doi: 10.3390/jpm14030319.
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.
基因组学已被预测将通过更好地理解人类疾病的分子机制来改善医疗,从而彻底改变人类健康。尽管过去十年全基因组关联研究(GWAS)取得了巨大成功,但其结果在转化为基因组医学方面仍较为有限。一条更接近改善医疗的途径可能是了解药物使用的遗传学。我们获取了英国生物银行中335744名个体的当前用药情况,并进行了全基因组关联研究以确定与当前用药相关的常见基因变异。总共确定了59个与用药相关的独立基因座,约18%的总变异可归因于常见基因变异。当前用药的遗传变异中最大一部分由低至中等次要等位基因频率的变异捕获,编码区、保守基因组区域和转录起始位点的相关变异更为丰富。用药情况与多基因评分之间的平均相关性(R)为0.14。结果进一步表明,用药多基因负担较高的个体平均病情更严重,药物不良反应风险更高。这些结果为药物使用的遗传贡献提供了见解,并为包括基于遗传信息的药物使用在内的新型多性状多基因评分的开发铺平了道路。