BACKGROUND: The development and approval of novel drugs are typically time-intensive and expensive. Leveraging a computational drug repurposing framework that integrates disease-relevant genetically regulated gene expression (GReX) and large longitudinal electronic medical record (EMR) databases can expedite the repositioning of existing medications. However, validating computational predictions of the drug repurposing framework remains a challenge. METHODS: To benchmark the drug repurposing framework, we first performed a 5-method-rank-based computational drug prioritization pipeline by integrating multi-tissue GReX associated with COVID-19-related hospitalization, with drug transcriptional signature libraries from the Library of Integrated Network-Based Cellular Signatures. We prioritized FDA-approved medications from the 10 top-ranked compounds, and assessed their association with COVID-19 incidence within the Veterans Health Administration (VHA) cohort (~9 million individuals). In parallel, we evaluated in vitro SARS-CoV-2 replication inhibition in human lung epithelial cells for the selected candidates. RESULTS: Our in silico pipeline identified seven FDA-approved drugs among the top ten candidates. Six (imiquimod, nelfinavir and saquinavir, everolimus, azathioprine, and retinol) had sufficient prescribing rates or feasibility for further testing. In the VHA cohort, azathioprine (odds ratio [OR]=0.69, 95% CI 0.62-0.77) and retinol (OR=0.81, 95% CI 0.72-0.92) were significantly associated with reduced COVID-19 incidence. Conversely, nelfinavir and saquinavir demonstrated potent SARS-CoV-2 inhibition in vitro (~95% and ~65% viral load reduction, respectively). No single compound showed robust protection in both in vivo and in vitro settings. CONCLUSIONS: These findings underscore the power of GReX-based drug repurposing in rapidly identifying existing therapies with potential clinical relevance; four out of six compounds showed a protective effect in one of the two validation approaches. Crucially, our results highlight how a complementary evaluation-combining epidemiological data and in vitro assays-helps refine the most promising candidates for subsequent mechanistic studies and clinical trials. This integrated validation approach may prove vital for accelerating therapeutic development against current and future health challenges.
A genetically based computational drug repurposing framework for rapid identification of candidate compounds: application to COVID-19.
基于基因的计算药物再利用框架,用于快速识别候选化合物:应用于 COVID-19
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作者:Voloudakis Georgios, Lee Kyung Min, Vicari James M, Zhang Wen, Hoagland Daisy, Venkatesh Sanan, Bian Jiantao, Anyfantakis Marios, Wu Zhenyi, Rahman Samir, Gao Lina, Cho Kelly, Lee Jennifer S, Iyengar Sudha K, Luoh Shiuh-Wen, Assimes Themistocles L, Hoffman Gabriel E, tenOever Benjamin R, Fullard John F, Lynch Julie A, Roussos Panos
| 期刊: | medRxiv | 影响因子: | 0.000 |
| 时间: | 2025 | 起止号: | 2025 Jan 14 |
| doi: | 10.1101/2025.01.10.25320348 | ||
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