{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"medRxiv"}],"indexed":{"date-parts":[[2026,10,28]],"date-time":"2026-10-28T00:10:29Z","timestamp":1793146229186,"version":"4.5.0"},"posted":{"date-parts":[[2025,1,14]]},"group-title":"Genetic and Genomic Medicine","reference-count":33,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2025,1,14]],"date-time":"2025-01-14T00:00:00Z","timestamp":1736812800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2025,1,14]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:sec>\n                  <jats:title>Background<\/jats:title>\n                  <jats:p>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.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>\n                    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\n                    <jats:italic>in vitro<\/jats:italic>\n                    SARS-CoV-2 replication inhibition in human lung epithelial cells for the selected candidates.\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>\n                    Our\n                    <jats:italic>in silico<\/jats:italic>\n                    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\u20130.77) and retinol (OR=0.81, 95% CI 0.72\u20130.92) were significantly associated with reduced COVID-19 incidence. Conversely, nelfinavir and saquinavir demonstrated potent SARS-CoV-2 inhibition\n                    <jats:italic>in vitro<\/jats:italic>\n                    (~95% and ~65% viral load reduction, respectively). No single compound showed robust protection in both\n                    <jats:italic>in vivo<\/jats:italic>\n                    and\n                    <jats:italic>in vitro<\/jats:italic>\n                    settings.\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>\n                    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\u2014combining epidemiological data and\n                    <jats:italic>in vitro<\/jats:italic>\n                    assays\u2014helps 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.\n                  <\/jats:p>\n                <\/jats:sec>","DOI":"10.1101\/2025.01.10.25320348","type":"posted-content","created":{"date-parts":[[2025,1,14]],"date-time":"2025-01-14T17:45:19Z","timestamp":1736876719000},"source":"Crossref","is-referenced-by-count":3,"title":["A genetically based computational drug repurposing framework for rapid identification of candidate compounds: application to COVID-19"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5729-632X","authenticated-orcid":false,"given":"Georgios","family":"Voloudakis","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8995-0448","authenticated-orcid":false,"given":"Kyung 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