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整合基因表达和临床数据,以鉴定用于高血脂和高血压的药物再利用候选物。

Integrating gene expression and clinical data to identify drug repurposing candidates for hyperlipidemia and hypertension.

机构信息

Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.

Medical Scientist Training Program, Vanderbilt University School of Medicine, Nashville, TN, USA.

出版信息

Nat Commun. 2022 Jan 10;13(1):46. doi: 10.1038/s41467-021-27751-1.

Abstract

Discovering novel uses for existing drugs, through drug repurposing, can reduce the time, costs, and risk of failure associated with new drug development. However, prioritizing drug repurposing candidates for downstream studies remains challenging. Here, we present a high-throughput approach to identify and validate drug repurposing candidates. This approach integrates human gene expression, drug perturbation, and clinical data from publicly available resources. We apply this approach to find drug repurposing candidates for two diseases, hyperlipidemia and hypertension. We screen >21,000 compounds and replicate ten approved drugs. We also identify 25 (seven for hyperlipidemia, eighteen for hypertension) drugs approved for other indications with therapeutic effects on clinically relevant biomarkers. For five of these drugs, the therapeutic effects are replicated in the All of Us Research Program database. We anticipate our approach will enable researchers to integrate multiple publicly available datasets to identify high priority drug repurposing opportunities for human diseases.

摘要

通过药物再利用发现现有药物的新用途可以减少新药开发相关的时间、成本和失败风险。然而,优先选择药物再利用候选物进行下游研究仍然具有挑战性。在这里,我们提出了一种高通量的方法来识别和验证药物再利用候选物。该方法整合了人类基因表达、药物干扰和来自公开资源的临床数据。我们将该方法应用于两种疾病高脂血症和高血压的药物再利用候选物的发现。我们筛选了超过 21000 种化合物,并复制了十种已批准的药物。我们还确定了 25 种(七种用于高脂血症,十八种用于高血压)其他适应症的药物,这些药物对临床相关生物标志物具有治疗效果。对于其中五种药物,在 All of Us Research Program 数据库中复制了其治疗效果。我们预计我们的方法将使研究人员能够整合多个公开可用的数据集,以确定针对人类疾病的高优先级药物再利用机会。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1f92/8748496/6523e800dfcf/41467_2021_27751_Fig1_HTML.jpg

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