Lee Kye Hwa, Baik Su Youn, Lee Soo Youn, Park Chan Hee, Park Paul J, Kim Ju Han
Seoul National University Biomedical Informatics (SNUBI), Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul 110799, Korea.
Department of Physiology and Cell Biology, University of Nevada School of Medicine, Reno, Nevada, United States of America.
PLoS One. 2016 Sep 30;11(9):e0162135. doi: 10.1371/journal.pone.0162135. eCollection 2016.
Despite substantial premarket efforts, a significant portion of approved drugs has been withdrawn from the market for safety reasons. The deleterious impact of nonsynonymous substitutions predicted by the SIFT algorithm on structure and function of drug-related proteins was evaluated for 2504 personal genomes. Both withdrawn (n = 154) and precautionary (Beers criteria (n = 90), and US FDA pharmacogenomic biomarkers (n = 96)) drugs showed significantly lower genomic deleteriousness scores (P < 0.001) compared to others (n = 752). Furthermore, the rates of drug withdrawals and precautions correlated significantly with the deleteriousness scores of the drugs (P < 0.01); this trend was confirmed for all drugs included in the withdrawal and precaution lists by the United Nations, European Medicines Agency, DrugBank, Beers criteria, and US FDA. Our findings suggest that the person-to-person genome sequence variability is a strong independent predictor of drug withdrawals and precautions. We propose novel measures of drug safety based on personal genome sequence analysis.
尽管在上市前进行了大量努力，但仍有相当一部分已获批药物因安全原因被撤出市场。针对2504个人类基因组，评估了SIFT算法预测的非同义替换对药物相关蛋白质结构和功能的有害影响。与其他药物（n = 752）相比，撤市药物（n = 154）和预防性药物（Beers标准，n = 90；美国食品药品监督管理局药物基因组生物标志物，n = 96）的基因组有害性得分显著更低（P < 0.001）。此外，药物撤市率和预防性措施与药物的有害性得分显著相关（P < 0.01）；联合国、欧洲药品管理局、DrugBank、Beers标准和美国食品药品监督管理局的撤市和预防性措施清单中包含的所有药物均证实了这一趋势。我们的研究结果表明，个体间的基因组序列变异性是药物撤市和预防性措施的一个强有力的独立预测指标。我们基于个人基因组序列分析提出了新的药物安全衡量标准。
