开发基因优先分数以利用人类遗传证据预测药物副作用
Áine Duffy1,2,3,4, Robert Chen1,2,3,5, David Stein1,2,3,6
1The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Nature communications
|September 30, 2025
概括
我们开发了一种计算工具,即副作用遗传优先分数 (SE-GPS),用于使用人类遗传数据预测药物副作用风险. 这一分数有助于在药物开发的早期确定潜在的安全问题.
科学领域:
- 药物基因组学 药物基因组学
- 计算生物学 计算生物学
- 药物发现 药物发现 药物发现
背景情况:
- 由于在临床试验中晚些时候发现的不可预见的安全问题,药物开发经常失败.
- 早期预测潜在的副作用对于有效和安全的药物开发至关重要.
研究的目的:
- 开发和验证一种in-silico方法,即副作用遗传优先评分 (SE-GPS),以预测药物向副作用风险.
- 利用人类遗传证据来优先考虑更有可能引起不良事件的药物标.
主要方法:
- 使用来自开放目标数据集的营销后副作用数据构建了SE-GPS.
- 在OnSIDES数据集中对SE-GPS进行了外部验证,并纳入了药物标签的副作用.
- 整合了遗传效应的定向性,以创建一个定向的SE-GPS (SE-GPS-DOE).
主要成果:
- 为19422个编码蛋白质的基因和502个发号生成了SE-GPS;1.7%超过了一个值.
- 使用至少两条遗传证据线增加了2.3倍 (开放目标) 和2.5倍 (侧面) 的副作用风险.
- 较高的SE-GPS得分与严重药物不良反应中丰富度增加相关.
结论:
- SE-GPS是一个有价值的计算工具,用于预测药物标安全性概况.
- 整合人类遗传证据可以显著改善早期识别潜在的药物副作用.
- 通过一个网页门户公开访问SE-GPS预测,以帮助药物发现工作.
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