{"doi":"10.1093/jamia/ocab165","title":"Computational drug repositioning of atorvastatin for ulcerative colitis","abstract":"OBJECTIVE: Ulcerative colitis (UC) is a chronic inflammatory disorder with limited effective therapeutic options for long-term treatment and disease maintenance. We hypothesized that a multi-cohort analysis of independent cohorts representing real-world heterogeneity of UC would identify a robust transcriptomic signature to improve identification of FDA-approved drugs that can be repurposed to treat patients with UC. MATERIALS AND METHODS: We performed a multi-cohort analysis of 272 colon biopsy transcriptome samples across 11 publicly available datasets to identify a robust UC disease gene signature. We compared the gene signature to in vitro transcriptomic profiles induced by 781 FDA-approved drugs to identify potential drug targets. We used a retrospective cohort study design modeled after a target trial to evaluate the protective effect of predicted drugs on colectomy risk in patients with UC from the Stanford Research Repository (STARR) database and Optum Clinformatics DataMart. RESULTS: Atorvastatin treatment had the highest inverse-correlation with the UC gene signature among non-oncolytic FDA-approved therapies. In both STARR (n = 827) and Optum (n = 7821), atorvastatin intake was significantly associated with a decreased risk of colectomy, a marker of treatment-refractory disease, compared to patients prescribed a comparator drug (STARR: HR = 0.47, P = .03; Optum: HR = 0.66, P = .03), irrespective of age and length of atorvastatin treatment. DISCUSSION & CONCLUSION: These findings suggest that atorvastatin may serve as a novel therapeutic option for ameliorating disease in patients with UC. Importantly, we provide a systematic framework for integrating publicly available heterogeneous molecular data with clinical data at a large scale to repurpose existing FDA-approved drugs for a wide range of human diseases.","journal":"Journal of the American Medical Informatics Association","year":2021,"id":167518,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":32,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9451,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":106158,"name":"Madeleine Scott","orcid":"0000-0001-9350-5451","position":1,"is_corresponding":false},{"id":268679,"name":"Ethan Steinberg","orcid":"0000-0001-7166-5032","position":2,"is_corresponding":false},{"id":657395,"name":"Laurynas Kalesinskas","orcid":"0000-0002-2903-2378","position":3,"is_corresponding":false},{"id":108094,"name":"Aida Habtezion","orcid":"0000-0002-4473-006X","position":4,"is_corresponding":false},{"id":226836,"name":"Nigam H. Shah","orcid":"0000-0001-9385-7158","position":5,"is_corresponding":false},{"id":4851,"name":"Purvesh Khatri","orcid":"0000-0002-4143-4708","position":6,"is_corresponding":false},{"id":501086,"name":"Lawrence Bai","orcid":"0000-0002-5617-9025","position":0,"is_corresponding":true}],"reference_count":92,"raw_metadata":null,"created_at":"2026-07-18T23:45:58.359801Z","pmid":"34529084","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}